docs: def custom_model(self, func):
          """ Run custom model provided by user.
  
          To Do,
          1. Define custom function's parameters, its data types, and return types
  
          Parameters
          ----------
          func    : function
              Custom function
  
          Returns
          -------
          dict
              Custom function's metrics
  
          """
  
          y_pred = func(self.baseline_in, self.baseline_out)
  
          self.custom_metrics = {}
          self.custom_metrics['r2'] = r2_score(self.baseline_out, y_pred)
          self.custom_metrics['mse'] = mean_squared_error(self.baseline_out, y_pred)
          self.custom_metrics['rmse'] = math.sqrt(self.custom_metrics['mse'])
          self.custom_metrics['adj_r2'] = self.adj_r2(self.custom_metrics['r2'], self.baseline_in.shape[0], self.baseline_in.shape[1])
  
          return self.custom_metrics